## Loading required package: DBI
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## Attaching package: 'dplyr'
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## The following object is masked from 'package:reshape':
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##     rename
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## The following objects are masked from 'package:stats':
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##     filter, lag
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## The following objects are masked from 'package:base':
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##     intersect, setdiff, setequal, union

Data standardization

Before standardization…

## Loading required package: lattice
## Loading required package: plyr
## -------------------------------------------------------------------------
## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)
## -------------------------------------------------------------------------
## 
## Attaching package: 'plyr'
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## The following objects are masked from 'package:dplyr':
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##     arrange, count, desc, failwith, id, mutate, rename, summarise,
##     summarize
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## The following objects are masked from 'package:reshape':
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##     rename, round_any

It’s very noisy so we simplify the charts…

Actually looks ok… may not need standardization

After standardization…

Auto-correlation

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## Attaching package: 'reshape2'
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## The following objects are masked from 'package:reshape':
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##     colsplit, melt, recast

Example: Auto-correlation for a single city: Boston

##      [,1]
## [1,]    0

Evaluate auto-correlation by the nth-day lagged.

14 days selected for best effect-dropoff.

Neighbors correlation

Neighborhoods

[ADD ME: plot convergence]

[FIXME: Graph is too close together]

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## Attaching package: 'igraph'
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##     %>%, as_data_frame, groups, union
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##     decompose, spectrum
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## [211] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

[ADD ME: Degree distribution]

## [1] 146

[ADD ME: Calculate statistical significance of lasso.coeffs.select]

Compare with SPACE results

## [1] "iter=1"
## [1] "iter=2"
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Evalute std_num_conflicts v. avg:same_region + avg:other_regions

[ADD ME: Some summary of results][FIX ME: Regress on each region, so each region’s effect is differentiated]

## [1] "iter 1"
## [1] "iter 2"
## [1] "iter 3"
## [1] "iter 4"
## [1] "iter 5"